{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import matplotlib.lines as mlines\n",
    "import matplotlib.colors as mcolors\n",
    "\n",
    "def get_color_code(color, percentile):\n",
    "    cmap = plt.get_cmap(color) \n",
    "    position = percentile / 100\n",
    "    rgba_color = cmap(position)\n",
    "    # Convert RGBA to RGB (since A is the alpha channel)\n",
    "    rgb_color = rgba_color[:3]  # Exclude the alpha value\n",
    "    # Convert RGB to hexadecimal color code\n",
    "    hex_color = mcolors.rgb2hex(rgb_color)\n",
    "    return hex_color\n",
    "\n",
    "num_heavy_atom = 9\n",
    "num_iterations = 200"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x800 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define functional groups to plot\n",
    "functional_groups = [\"carbonyl\", \"amide\", \"carbamide\"]\n",
    "\n",
    "# Create subplots\n",
    "fig, axes = plt.subplots(1, 3, figsize=(15, 8), dpi=100)\n",
    "\n",
    "for i, functional_group in enumerate(functional_groups):\n",
    "    ax = axes[i]  # Get the current subplot axis\n",
    "    \n",
    "    # File paths\n",
    "    data_path_chem = f\"../results_chemistry_constraint_bo/{functional_group}_{num_heavy_atom}_chem_1.csv\"\n",
    "    data_path_no_chem = f\"../results_no_chemistry_constraint_bo/{functional_group}_{num_heavy_atom}_no_chem_1.csv\"\n",
    "    \n",
    "    # Read data\n",
    "    trial_df_chem = pd.read_csv(data_path_chem)\n",
    "    trial_df_chem['trial_index'] = trial_df_chem['trial_index'] - 4\n",
    "    trial_df_chem = trial_df_chem.iloc[5:num_iterations+5]\n",
    "    \n",
    "    trial_df_no_chem = pd.read_csv(data_path_no_chem)\n",
    "    trial_df_no_chem['trial_index'] = trial_df_no_chem['trial_index'] - 4\n",
    "    trial_df_no_chem = trial_df_no_chem.iloc[5:num_iterations+5]\n",
    "    \n",
    "    # Scatter plot with color based on 'trial_index' column\n",
    "    scatter_chem = ax.scatter(trial_df_chem['qed'], trial_df_chem['product_validity_uniqueness'], c=trial_df_chem['trial_index'], \n",
    "                              cmap='Reds', s=10, label=\"w/ chemistry\\nconstraint\")\n",
    "    scatter_no_chem = ax.scatter(trial_df_no_chem['qed'], trial_df_no_chem['product_validity_uniqueness'], c=trial_df_no_chem['trial_index'], \n",
    "                                 cmap='Blues', s=10, label=\"w/o chemistry\\nconstraint\")\n",
    "    \n",
    "    # Adding colorbar with integer ticks\n",
    "    z_min, z_max = int(trial_df_chem['trial_index'].min()), int(trial_df_chem['trial_index'].max())\n",
    "    colorbar_1 = fig.colorbar(scatter_chem, ax=ax, ticks=list(np.arange(z_min, z_max + 1, 20))+[200], orientation='horizontal')\n",
    "    colorbar_2 = plt.colorbar(scatter_no_chem, ticks=list(np.arange(z_min, z_max + 1, 20))+[200], orientation='horizontal')\n",
    "    colorbar_1.set_label('Iteration', fontsize=14, weight='semibold')\n",
    "    \n",
    "    # Legend with proxy artists\n",
    "    red_proxy = mlines.Line2D([], [], color=get_color_code(\"Reds\", num_iterations / 2), marker='.', linestyle='None', markersize=10, label=\"w/ chemistry\\nconstraint\")\n",
    "    blue_proxy = mlines.Line2D([], [], color=get_color_code(\"Blues\", num_iterations / 2), marker='.', linestyle='None', markersize=10, label=\"w/o chemistry\\nconstraint\")\n",
    "    if i == 0:\n",
    "        ax.legend(handles=[red_proxy, blue_proxy], loc=\"upper left\")\n",
    "    \n",
    "    # Set labels with appropriate font sizes\n",
    "    ax.set_xlabel('Average QED score (-)', fontsize=16, weight='semibold')\n",
    "    if i == 0:\n",
    "        ax.set_ylabel(\"Validity $\\\\times$ uniqueness (-)\", fontsize=16, weight='semibold')\n",
    "    else:\n",
    "        ax.set_ylabel(None)\n",
    "    \n",
    "    # Adjust tick parameters\n",
    "    ax.set_xticks(np.arange(0, 0.7, 0.1))\n",
    "    ax.set_yticks(np.arange(0, 0.5, 0.05))\n",
    "    ax.tick_params(axis='both', which='major', labelsize=12)\n",
    "    \n",
    "    # Remove top and right spines for a cleaner look\n",
    "    ax.spines['top'].set_visible(False)\n",
    "    ax.spines['right'].set_visible(False)\n",
    "    \n",
    "    # Set the title for each subplot based on functional group\n",
    "    ax.set_title(f\"{functional_group.capitalize()}\", fontsize=14, weight='semibold')\n",
    "\n",
    "# Tight layout for optimal spacing\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"figures/mpo.svg\", format=\"svg\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "# functional_group_index = {\"carbonyl\": {\"before_index\":0, \"after_index_chem\":54, \"after_index_no_chem\": 54},\n",
    "#                           \"carbamide\": {\"before_index\":0, \"after_index_chem\":47, \"after_index_no_chem\": 53},\n",
    "#                           \"amide\": {\"before_index\":0, \"after_index_chem\":53, \"after_index_no_chem\": 54}\n",
    "#                           }\n",
    "functional_group_index = {\"carbonyl\": {\"before_index\":0, \"after_index_chem\":200, \"after_index_no_chem\": 200},\n",
    "                          \"carbamide\": {\"before_index\":0, \"after_index_chem\":200, \"after_index_no_chem\": 200},\n",
    "                          \"amide\": {\"before_index\":0, \"after_index_chem\":200, \"after_index_no_chem\": 200}\n",
    "                          }\n",
    "\n",
    "functional_group_distribution_list = []\n",
    "for functional_group in functional_groups:\n",
    "    sub_list = []\n",
    "    for index_name in [\"before_index\", \"after_index_no_chem\", \"after_index_chem\"]:\n",
    "        index = functional_group_index[functional_group][index_name]\n",
    "        if index_name in [\"before_index\", \"after_index_no_chem\"]:\n",
    "            file_name = f\"../results_no_chemistry_constraint_bo/sample_{functional_group}_{num_heavy_atom}_no_chem_1_{index}.pkl\"\n",
    "        else:\n",
    "            file_name = f\"../results_chemistry_constraint_bo/sample_{functional_group}_{num_heavy_atom}_chem_1_{index}.pkl\"\n",
    "        with open(file_name, \"rb\") as f:\n",
    "            data = pickle.load(f)\n",
    "        sub_list.append(data)\n",
    "    functional_group_distribution_list.append(sub_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append(\"../\")\n",
    "from qmg.generator import MoleculeGenerator\n",
    "from qmg.utils import ConditionalWeightsGenerator, FitnessCalculator\n",
    "\n",
    "fitness_distribution_list = []\n",
    "fc = FitnessCalculator(task=\"qed\")\n",
    "\n",
    "for i in range(len(functional_group_distribution_list)):\n",
    "    sub_list = []\n",
    "    for j in range(len(functional_group_distribution_list[0])):\n",
    "        smiles_dict = functional_group_distribution_list[i][j]\n",
    "        data_distribution = fc.generate_property_distribution(smiles_dict)\n",
    "        sub_list.append(data_distribution)\n",
    "    fitness_distribution_list.append(sub_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.colors as mcolors\n",
    "import numpy as np\n",
    "\n",
    "def get_color_code(color, percentile):\n",
    "    cmap = plt.get_cmap(color)\n",
    "    position = percentile / 100\n",
    "    rgba_color = cmap(position)\n",
    "    rgb_color = rgba_color[:3]  # Exclude the alpha value\n",
    "    hex_color = mcolors.rgb2hex(rgb_color)\n",
    "    return hex_color\n",
    "\n",
    "# Create subplots\n",
    "fig, axes = plt.subplots(1, 3, figsize=(15, 5))\n",
    "bins = np.linspace(0, 0.65, 75)\n",
    "\n",
    "for i, functional_group in enumerate(functional_groups):\n",
    "    ax = axes[i]  # Select the subplot axis\n",
    "    \n",
    "    # Plot histograms with adjusted styles for each subplot\n",
    "    \n",
    "    ax.hist(\n",
    "        fitness_distribution_list[i][2],\n",
    "        bins=bins,\n",
    "        color=get_color_code(\"Reds\", 90), \n",
    "        edgecolor='black',\n",
    "        linewidth=0.5,\n",
    "        alpha=0.5,\n",
    "        label='After BO w/\\nchemistry constraint'\n",
    "    )\n",
    "    ax.hist(\n",
    "        fitness_distribution_list[i][1],\n",
    "        bins=bins,\n",
    "        color=get_color_code(\"Blues\", 90), \n",
    "        edgecolor='black',\n",
    "        linewidth=0.5,\n",
    "        alpha=0.5,\n",
    "        label='After BO w/o\\nchemistry constraint'\n",
    "    )\n",
    "    ax.hist(\n",
    "        fitness_distribution_list[i][0],\n",
    "        bins=bins,\n",
    "        color=get_color_code(\"Reds\", 0),\n",
    "        edgecolor='black',\n",
    "        linewidth=0.5,\n",
    "        alpha=0.85,\n",
    "        label='Before BO'\n",
    "    )\n",
    "    # Label axes\n",
    "    ax.set_xlabel('QED Score (-)', fontsize=16, weight='semibold')\n",
    "    ax.set_ylabel('Count (-)', fontsize=16, weight='semibold')\n",
    "    ax.set_xticks(np.arange(0, 0.8, 0.1))\n",
    "    ax.set_yticks(np.arange(0, 320, 50))\n",
    "    ax.spines['top'].set_visible(False)\n",
    "    ax.spines['right'].set_visible(False)\n",
    "\n",
    "    # Add legend\n",
    "    if i == 0:\n",
    "        # Get the current handles and labels from the plot\n",
    "        handles, labels = ax.get_legend_handles_labels()\n",
    "        # Reorder the handles and labels (e.g., if you want to swap the first and last labels)\n",
    "        order = [2, 1, 0]  # Specify the new order of labels\n",
    "        ax.legend([handles[i] for i in order], [labels[i] for i in order], frameon=False, fontsize=12, loc=\"upper left\")\n",
    "\n",
    "\n",
    "    # Set the title for each subplot\n",
    "    ax.set_title(f\"{functional_group.capitalize()}\", fontsize=14, weight='semibold')\n",
    "\n",
    "# Adjust layout to prevent clipping\n",
    "plt.tight_layout()\n",
    "# Save the figure in a vector format (optional)\n",
    "plt.savefig('figures/propery_distribution.svg', format='svg')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 carbonyl\n",
      "After BO w/o chemistry constraint\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'C=CCC(=O)O': 0.5006970737992, 'C=CC1=CC(=O)N1': 0.4944206116502758, 'CCC(=O)O': 0.4908446664452932, 'C=CNC(C)=O': 0.48605367287207835, 'C=Cc1cc1=O': 0.4815179071694712, 'C=CC1=CC(=O)C1': 0.47469529660525783, 'C=NCC(=O)O': 0.4728189142118678, 'C=CCC(N)=O': 0.47278472146091227, 'O=C(O)C1=C=N1': 0.47017074327751535, 'C=CC(=O)CO': 0.4696852142405516}\n",
      "After BO w/ chemistry constraint\n",
      "{'CC[C@H](C)[C@@H](C)C(=O)O': 0.6315729529430132, 'CCC[C@H](C)CC(=O)O': 0.6306362992241078, 'CCC[C@H](CC)C(=O)O': 0.6306362992241078, 'CCC[C@@H](CC)C(=O)O': 0.6306362992241078, 'CCCC[C@H](C)C(=O)O': 0.6306362992241077, 'CC[C@@H]1C[C@@H]1CC(=O)O': 0.6250858180201716, 'CC[C@@H](C(=O)O)[C@@H]1CC1': 0.6250858180201716, 'CCC(=O)[C@](C)(O)CC': 0.6213627168866812, 'CC[C@@](N)(CC)C(C)=O': 0.6195522024118125, 'CCC(=O)[C@](C)(N)CC': 0.6195522024118125}\n",
      "1 amide\n",
      "After BO w/o chemistry constraint\n",
      "{'CCCCC(N)=O': 0.5572457708532276, 'CCCOC(N)=O': 0.5526104216706519, 'C[C@@H](C)CC(N)=O': 0.5409744937836245, 'CC[C@@H](C)C(N)=O': 0.5409744937836245, 'CC[C@H](C)C(N)=O': 0.5409744937836245, 'C=CNC(=O)CC': 0.5408977604148096, 'CCNC(=O)CC': 0.5398542153220982, 'CCCNC(C)=O': 0.5398542153220982, 'CCCC(=O)NC': 0.5398542153220982, 'CCCNC(=O)O': 0.539100637864967}\n",
      "After BO w/ chemistry constraint\n",
      "{'CCCOC(=O)NCC': 0.6233963277139051, 'C/C=C\\\\NC(=O)CCC': 0.6102391075233103, 'CC[C@H](C)NC(=O)OC': 0.6099184307112384, 'CCCCC(=O)NCC': 0.6089376691121774, 'CCC[C@]1(C)NC(=O)O1': 0.6088061037738778, 'CCNC(=O)[C@H](C)CC': 0.6085485466371162, 'CCN(C(=O)O)[C@@H]1CC1': 0.607135490260851, 'CCCN(CC)C(N)=O': 0.6030305506803478, 'CC/C=C(\\\\C)NC(C)=O': 0.5970785934690973, 'C/C=C\\\\NC(=O)COC': 0.5941307052362604}\n",
      "2 carbamide\n",
      "After BO w/o chemistry constraint\n",
      "{'CCN(C(N)=O)[C@@H]1CC1': 0.5796044772677978, 'O=NC(=O)Nc1c2on1-2': 0.5719237069595422, 'CC/C=C\\\\NC(=O)N=O': 0.5709538730407734, 'Cn1cc(NC(N)=O)o1': 0.5643035898112193, 'CNc1cn(C(N)=O)o1': 0.5622287280355368, 'CCC1=C(NC(N)=O)O1': 0.5598513153067517, 'N=NC(=O)Nc1c2on1-2': 0.5571321821864648, 'O=C1N=NN1[C@@H]1n2[nH]n21': 0.5527126549612976, 'CCC1=CN(C(N)=O)C1': 0.5512344854606404, 'COC1=C(NC(N)=O)C1': 0.5457543080603144}\n",
      "After BO w/ chemistry constraint\n",
      "{'CCCn1cc[nH]c1=O': 0.6182467487366656, 'CO[C@@H](C)n1o[nH]c1=O': 0.6124967496701142, 'CCCCC1=NC(=O)N1': 0.6079775489228005, 'CCCn1nc[nH]c1=O': 0.6066577208974667, 'CCCn1cn[nH]c1=O': 0.6066577208974667, 'CCCCn1[nH][nH]c1=O': 0.6057335349689758, 'C=CN(CCC)C(N)=O': 0.6032096452786023, 'CCCN(CC)C(N)=O': 0.6030305506803478, 'CCCCN(C)C(N)=O': 0.6030305506803478, 'CCn1[nH]c(=O)n1CC': 0.6005390709694024}\n"
     ]
    }
   ],
   "source": [
    "for i, functional_group in enumerate(functional_groups):\n",
    "    print(i, functional_group)\n",
    "    for j in range(len(functional_group_distribution_list[0])):\n",
    "        if j == 0:\n",
    "            continue\n",
    "        if j == 1:\n",
    "            print(\"After BO w/o chemistry constraint\")\n",
    "        if j == 2:\n",
    "            print(\"After BO w/ chemistry constraint\")\n",
    "        smiles_dict = functional_group_distribution_list[i][j]\n",
    "        prop_dict = fc.generate_property_dict(smiles_dict)\n",
    "        top_10 = dict(sorted(prop_dict.items(), key=lambda item: item[1], reverse=True)[:10])\n",
    "        print(top_10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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